IMPLICATION OF GENE ACTION AND HERITABILITY UNDER STRESS AND CONTROL CONDITIONS FOR SELECTION IRON TOXICITY TOLERANT IN RICE

  282

  

AGRIVITA Journal of Agricultural Science. 2016. 38(3): 282-295

  

IMPLICATION OF GENE ACTION AND HERITABILITY UNDER STRESS

AND CONTROL CONDITIONS FOR SELECTION IRON TOXICITY TOLERANT IN RICE

  Yudhistira Nugraha 1,2) , Sintho Wahyuning Ardie 2) , Suwarno 1) , Munif Ghulamahdi 2) and Hajrial Aswidinnoor 2*) 1) Indonesian Agency for Agricultural Research and Development

  Jl. Pasar Minggu Jakarta 12540, Indonesia 2) Department Agronomy and Horticulture, Faculty of Agriculture, Bogor Agricultural University (IPB)

  Jl. Meranti Kampus Darmaga Bogor 16680, Indonesia *)

  

Corresponding author E-mail: hajrial@ipb.ac.id

Received: December 2, 2015 /Accepted: July 29, 2016

  ABSTRACT

  Iron toxicity is major constraint of rice production in irrigated-lowland. The Improvement of tolerant rice cultivar to iron toxicity requires the information of some genetics parameters related to selected characters. This study was aimed to estimate gene action and heritability of the grain yield and its component under iron-toxic stress and control field conditions in rice. The iron-toxic tolerant rice cultivars, Pokkali and Mahsuri were crossed with the sensitive cultivar, Inpara5 to develop six generation populations. The breeding materials were grown in the iron toxicity site and control in Taman Bogo, Lampung Indonesia in the wet season from December 2013 to March 2014. The sensitive parent and BC 1 P 1 had lower stress tolerance index (STI) compared to the tolerant parent F 1 , F 2 and BC 1 P 2 . The grain yield and its component were fitted to the best model in five parameters which were more prominent with interactive epistasis of duplicate and comple- the economic, political and social-life. Indonesian government needs to insure the self-sufficient of rice by increasing rice production, which more than 51.7% of rice production is produced in Java Island (Statistics Indonesia, 2015). The remaining areas of Indonesian paddy field are located outside Java, which they are predominantly as an old-weathered soil or Ultisols soil (Prasetyo & Suriadikarta, 2006) and tidal swampy-land (Muhrizal, Shamshuddin, Fauziah, & Husni, 2006). One of the characteristic of these soils is abundant of iron-oxide in mineral soil formation. During flooded conditions where most of rice is cultivated, this soil mineral can be changed into ferrous ion (Fe 2+ ). This formation is more soluble and ready to be uptaken by plant and resulting a toxic condition to rice plant when it is excessive. The Fe 2+ concentrations in the soil solution that can affect lowland-rice yields are ranging from 10 to >5000 mg L

  • –1

  (Becker & Asch, 2005). However, it is generally considered that a soil solution

  • –1

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  Yudhistira Nugraha et al.: Implication of Gene Action and Heritability Under Stress and Control Conditions ……………

  Meanwhile, in Indonesia there is no recent data about the total area of low-land rice affected to iron toxicity, but Ismunadji (1990) roughly estimated about 1 million ha, which predominantly consisted with acidic soil and tidal swampy land. Since it is quit huge areas, it is greatly important to increase rice production of these areas to meet the growing demand of rice in Indonesia.

  The best way to minimize the iron toxicity effect in rice is using tolerant cultivar (Stein, Lopes, & Fett, 2014). Most of the modern semi- dwarf high yielding rice cultivars were sensitive to iron toxicity (Wade, Fukai, Samson, Ali, & Mazid, 1999), whereas the tolerant varieties were mostly identified as a land race and wide species (Onaga, Egdane, Edema, & Abdelbagi, 2013). Introducing the iron toxicity tolerant traits into modern cultivars is very important to develop simultaneously a high yield and tolerant to iron toxicity cultivars.

  In the breeder point of view, the estimation of genetics parameters such as, heritability, gene action and correlation among charact ers’ are very important in order to formulate the most advan- tageous breeding procedures. The genetic studies on iron toxicity both using classical and molecular approach in rice were reported referring to complex inheritance and govern by many genes (Dufey, Hakizimana, Draye, Lutts, & Bertin, 2009; Dufey et al., 2015; Shimizu, 2009; Wan, Zhai, Wan, & Ikehashi, 2003; Wu et al., 2014). Those genetics studies mostly were conducted only under one site environment in the controlled greenhouse or the iron-toxic stress conditions in the field, but they never compared to the controlled environments. accessible for conducting field screening, in Indonesia e.g. Sumatera, Kalimantan and Papua where it is far from research center. It is, therefore, very important for comparing the genetic parameters from the generation mean analysis under various environments. The result from this genetics study would lead the breeder to answer the question should the selection be done under the stressed condition or in-house experimental farm or under control condition.

  This study was extrapolated the inheritance of some agronomy and the grain yield traits under natural field condition with high iron concentration and control sites. The populations of crosses

  Pokkali, an iron-tolerant variety with robust

  development of seedling type (Engel, Asch, & Becker, 2012) and excluder-tolerant type (Wu et al., 2014) and Mahsuri, an iron toxicity tolerant varieties well known in Indonesia (Suhartini & Makarim, 2009) were used to in generation mean analysis (Mather & Jinks, 1982). The information of this current study would improve the understanding of inheritance of iron toxicity tolerance in rice as well as facilitate planning possible breeding programs. In this study gene action, heritability, and correlation among related traits were measured.

  MATERIALS AND METHODS Plant Materials and Experimental Site

  The rice variety Pokkali and Mahsuri were used as tolerant parents to iron toxicity, while

  Inpara5 as sensitive parent. The varieties were

  crossed in a resulting of populations each composed of six generations per cross the

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  Yudhistira Nugraha et al.: Implication of Gene Action and Heritability Under Stress and Control Conditions …………… season from December, 2013 to March, 2014.

  The experiment site has Af climate-type (Köppen- Geiger classification), average temperature is

  26.9 o

  C, and annual rainfall is 2,143 mm. Two plots were used for iron toxicity site and control site. The iron toxicity site has been identified as a natural Fe toxicity when it is flooded. Variations in soil iron content between the two plots were expected due to position difference in the topo- sequence. Four soil samples from the field (each a composite of at least three sub-samples) are showed in Table 1.

  Experimental Design and Cultural Practices

  Common agronomic practices for rice growing, including plowing, harrowing, and flooding was done both in the experimental site. The basal fertilizer was broadcasted at the rate of 46 kg N ha

  • -1 and 36 kg P
  • 2 O 5 ha -1 and 45 kg K 1. 2 O ha -

    • – 2B
    • 1 – 2B 2 [d]= ½P 1 – ½/P 2 ; = 6B 1 + 6B 2 – 8F 2 – F 1 – 1½P 1 1½P 2 [i] = 2B 1 + 2B 2 – 4F 2 [j] = 2B 1

        The N fertilizer application was given additionally at 3 weeks after transplanting at the rate of 23 kg N ha -1 . The iron toxic plot was kept submerged at depth 10-15 cm water to prevent oxidation of Fe 2+ to Fe 3+ . The observed parameters were measured to 20 of F 1 , 100 of BC 1 P 1 , and BC 1 P 2 and 250 of F 2 population.

      • – P
      • 1 – 2B 2 +P 2 [l] = P 1 + P 2 + 2F 1 + 4F 2 – 4B 1 – 4B 2 This equation includes the contribution of a

          Data Recording, Measurement and Analysis

          Each plant in all population was tagged and given a number to make sure that the measurement of all observed characters was indicated to the same plant. The leaf bronzing score (LBS) was scored non-destructively at 6 weeks after transplanting for leaf bronzing using the SES developed by IRRI (IRRI, 1996). Plant height was determined by measuring the height from base of the shoot to the highest tip of panicle. The grain per plant was hand-threshed of all panicles. The filled grains were separated and counted to weights for determining 100-grain weight. The grain yields then were adjusted to a moisture concentration of 14% of fresh weight. The grain numbers were defined by divided the grain yield per plant with its respective 100-grain weight per 100.

          A joint-scale test was performed using chi- square goodness of fit with three degrees of freedom as described by (Cavalli, 1952). When the three-parameters individual-scaling model did not show conformity of additive dominance (i.e. with values different from zero), a six-parameter scaling model was performed as:

          m = ½P 1 +½P 2 + 4F 2

          digenic epistasis (nonallelic interaction). The test provides estimates for three parameters mid- parent m, additive effect [d], dominance effect but also provides estimates for three epistasis parameters; additive x additive [i]; additive x dominance [j] and dominance x dominance [l]. A significant level (P ≤ 0.05) was used to compare all components. The three- and six-parameter models were developed as described by Mather & Jinks (1982).

          nF 1 = number of plants of F 1 generations Ne= effective population size, where Ne = nP 1 + nP 2 + nF1, i.e. number of P 1 , P 2 and F 1 ,

          The means and standard errors for parents, F 1 , F 2 and backcross generations under iron toxicity and control condition are presented in Table 2. Both parents showed contrasting performance under different environment except for, tiller number in Cross 1 and 100-grain weight in Cross 2 both in control condition. The F 1 of both crosses had mean value between the superior and lower parents in all environments, except for grain yield, which presented the heterobeltiosis in this generation. The mean value of F 2 were also between the parents but lower than that of the F 1 in all experiment and crosses. In general, mean of BC to superior parent were greater than the mean of BC to the lower parent and F 1 in all the crosses and environments. The transgressive segregations from the mean value were observed in the population of F 2 , BC 1 P 1 and BC 2 P 2 , indicating a contrasting used parent in the crosses.

          Yudhistira Nugraha et al.: Implication of Gene Action and Heritability Under Stress and Control Conditions ……………

          Broad-sense heritability was estimated using the method described by Fehr (1987) as

          h 2 bs = σ 2 g / ( σ 2 g + σ 2 e ). The estimate of genetic

          variance 2 g ) is equal to the variance of F 2 generation (σ 2 F 2 ) minus the environmental variance ( σ 2 e ). In this formula:

          σ 2 e = [nP 1 σ 2 P 2 + nP 2 σ 2 P2 + nF 1 σ 2 F 1 ]/Ne

          Where:

          nP 1 = number of plants of sensitive parents (P 1 ) nP 2

          = number of plants of resistant parents (P 2 )

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          respectively The method used to estimate narrow- sense heritability was adapted from (Fehr, 1987) as:

          h 2 ns = [2(σ 2 F 2 )

        • – (σ
        • 2 BC 1<

          • + σ
          • 2 BC 2 )/σ 2 F 2 Where: σ 2 F 2 = variance among F 2 individuals σ 2 BC 1

            σ 2 BC 2 = variances of BCP 2 generations

            Correlation between related traits was performed using simple Pearson correlation.

            The statistical analyses were done using SAS/STAT® version 9.1. (SAS Institute, 2004). The SAS listing program for the scaling test of three and six parameters and heritability analysis were developed by Gusti N. Adi-wibawa (Supplemental data 2).

            = variances of BCP 1 generations

            The cross population of Inpara5 x Pokkali had high STI index in most of characters in all generation compared to cross population of Inpara5 x Mahsuri, except for number of grain. The highest STI in both of crosses (Table 2) was revealed in the 100-grain weight indicating that this characters less effected by iron toxicity conditions ranging from (0.91-1.00). Both of tolerant parents, Mahsuri and Pokkali displayed more adaptability to stress condition by performing higher STI compared to sensitive parent, Inpara5 in all characters. Meanwhile, the STI of F 1 generation were between the two contrasting parents indicating the presence of mid-parent heterotic in all characters. Iron toxic stress condition showed more affected in most observed

          RESULTS AND DISCUSSION

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            Yudhistira Nugraha et al.: Implication of Gene Action and Heritability Under Stress and Control Conditions ……………

            additive [d] and dominance [h] indicating partially dominant to the alleles that decreasing grain weight. For this cross, additive [d] gene effects were the most important factor (p&lt;0.001) contributing to the genetic control, while dominance (h] gene effects were also significant but smaller in magnitude.

            For the other characters in different crosses and environment, the significant χ 2 obtained from the joint-scaling tests suggested that the three-parameter model was not adequate in explaining the variability present and thus other more complex models were necessary to accommodate the presence of epistasis. These characters best fitted to five parameters model involving mixed epistasis interaction of additive x additive [i], additive x dominance [j], dominance x dominance [l], in addition to additive [i] and dominance [i] components but these were depending on the crosses and environments (Table 3 and Table 4).

            For the number of grain and grain yield of Cross 1 and Cross 2, and 100-grain of Cross 2 under iron toxicity condition the best-fit model were epistasis interaction additive x dominance [j] and dominance x dominance [l], in addition to additive [i] and dominance [i] and the largest gene effect was to dominance x dominance. This type of interactive epistasis also presented in control condition for tiller number, grain yield of both Crosses and 100-grain weight, where its magnitude of gene effect were duplicate pointing towards the iron-sensitive parent. Tiller number of all cross under control condition and 100-grain weight of Cross 2 under all environment had best- fitted using five model parameters involving of control condition, the interactive model dominance x dominance effects [l] were significant and had opposite sign to those of dominance effects alone

            [h], indicating the presence of a duplicate type of

            epistasis. This type of epistasis and higher magnitudes of [h] and [l] in the population has implication in reducing the efficiency of selection. Under this condition the selection would be effective after late generations once a high level of gene fixation is attained for the traits showing significant gene interactions. Signs associated with different estimates of epistasis indicate the direction in which gene effects influence the population mean. Kearsey &amp; Pooni (1996) proposed the association or dispersion of genes in the parents based on signs of dominance [h] and interactive gene effects of dominance x dominance [l]. In this present study, the signs of

            [h] in most of traits were negative both in Fe

            toxicity and control which suggested that a large influence of the recessive parent. Such dispersion with more recessive genes compared to dominant genes has been observed in three from six crosses of spring wheat under manganese toxicity condition (Moroni, Briggs, Blenis, &amp; Taylor, 2013).

            For the other characters presented of interactive effect of [i], [j] and [l] resulting an epistasis gene of duplicate and complementary (Table 3 and Table 4). The type of epistasis depending on the cross, environment and sometime resulting interaction between both of them (Cao et al., 2001). This gene action complexity indicated that improvement of the characters studied would be moderately difficulty as compared to the situation pertaining had an additive-dominance model (best from a breeders Table 2. Mean, deviation and stress tolerance index (STI) per plant of population P 1 , P 2 , F 1 , F 2 , BC 1 P 1 and BC 1 P 2 of rice seedling of Inpara5 x Mahsuri (Cross 1) and Inpara5 x Pokkali (Cross 2) under iron toxicity and control condition

            Population Plant height (cm) (Mean SD) STI Tiller number (no) (Mean SD) STI 100-GW (g) (Mean SD) STI C S C S C S Cross 1 P 1 101.1±4.4 66.9±6.9

          0.62 16.2±3.5 7.1±3.0

          0.44 2.4±0.14 2.2±0.14

            0.29 P 2 230.1±11.1 192.2±28.9 0.83 12.4±2.0 10.0±2.2

            0.62 Remarks: N= control condition; S= stress condition; STI= stress tolerance index; ± = standard deviation of means 287

            0.52 BCP 2 148.5±9.8 76.4±23.4 0.60 12.1±3.1 7.6±3.4

            0.60 BCP 1 127.8±15.8 59.4±23.2 0.40 12.6±3.1 6.2±3.5

            0.65 F 2 135.4±25.9 67.4±25±4 0.50 12.3±3.5 7.2±3.5

            0.91 F 1 145.5±6.9 94.8±16.4 0.65 17.1±2.3 11.0±2.4

            0.31 P 2 146.7±10.7 105.4±17.9 0.72 11.8±2.6 10.4±2.5

            0.70 Cross 2 P 1 124.5±8.3 52.3±12.5 0.42 15.2±2.7 4.60±2.0

            0.49 BCP 2 191.5±33.1 146.8±46.9 0.92 13.0±4.0 9.2±4.1

            0.62 BCP 1 159.7±28.2 109.5±51.2 0.57 14.1±3.4 6.9±3.6

            0.75 F 2 178.3±38.6 122.3±57.4 0.69 13.9±3.9 8.0±4.3

            0.82 F 1 204.5±19.1 173.1±29.1 0.85 16.4±2.4 12.6±2.9

            Cross 1 P 1 125.7 ±16.1 56.1±23.7 0.45 15.5±2.3 4.5 ±2.0

            0.92 P 2 140.4±4.9 105.5±7.8

          0.75 14.6±2.6 12.9±2.2

          0.86 1.6±0.02 1.6±0.09

             SD) STI C S C S

            1.00 Table 2. (continued) Population Grain number (no) (Mean SD) STI Grain yield (g) (Mean

            0.96 BCP 2 136.7±9.3 127.0±17.0

          0.93 11.3±2.9 8.2±4.0

          0.75 2.7±0.19 2.7±0.19

            0.96 BCP 1 120.7±12.1 100.1±19.7

          0.83 10.3±2.7 6.2±3.4

          0.62 2.6±0.23 2.5±0.22

            1.00 F 2 129.2±14.2 109.1±21.1

          0.84 11.0±3.4 8.8±4.1

          0.88 2.6±0.26 2.5±0.24

            1.00 F 1 136.6±7.1 119.6±7.1

          0.88 13.8±1.6 10.5±3.0

          0.77 3.0±0.17 2.9±0.12

            0.96 P 2 140.4±6.1 126.8±9.3

          0.90 10.0±2.1 10.6±2.6

          0.96 3.0±0.09 3.0±0.16

            1.00 Cross 2 P 1 104.0±6.5 68.1±9.3

          0.65 14.8±2.3 6.8±1.8

          0.49 2.4±0.08 2.3±0.11

            0.91 BCP 2 139.9±8.8 101.3±17.9

          0.68 14.4±3.8 10.7±4.1

          0.71 1.9±0.22 1.9±0.20

            1.00 BCP 1 119.3±10.2 83.4±11.1

          0.67 17.1±5.2 8.9±3.8

          0.52 2.3±0.22 2.2±0.21

            0.91 F 2 129.2±13.4 92.9±18.2

          0.63 15.4±4.9 8.4±4.4

          0.56 2.2±0.24 2.1±0.23

            1.00 F 1 138.9±4.4 102.3±6.4

          0.74 20.7±2.9 12.9±2.6

          0.60 2.3±0.05 2.1±0.10

            Yudhis tira N ugraha e t al .: Im plic a tion o f Gene A c tio n and H eri tabilit y U nder S tres s and C on trol C ondit ions …………… Table 3. Joint scaling test with three parameter model (m, [d], [h]) and estimates of the components of the six generation means of fitted to a six parameter model of rice population from the cross of Inpara5 x Mahsuri (Cross 1) and Inpara 5 x Pokkali (Cross 2) under iron toxicity condition in the field

          11.15 NS

            19.27±1.14** - 2.94±0.42** 1.54±0.30** - 0.31±0.01** [h] 9.87±4.75* - 8.91±1.21** -18.06±3.91** - -0.58±0.08** [i] - - 6.04±0.83** -6.08±1.37** - - [j]

            tira N ugraha et al .: Im pli c at ion of Gene Ac tio n and H eri tabilit y U nder St re s s and C on trol C on dit ions ……………….

            Parameter a Plant height (cm) Tiller number (no) 100-grain weight (g) Cross 1 Cross 2 Cross 1 Cross 2 Cross 1 Cross 2

            Three parameter m 86.03±0.99** 98.57±1.16** 8.53±0.36** 7.81±0.32** 1.92±0.02** 2.51±0.02 ** [d]

            12.84±1.03** 29.16±1.20** 2.23±0.35** 1.29±0.30 ** -0.35±0.02** 0.29±0.02 ** [h] 14.19±1.81** 22.72±2.06** 1.8±0.67* 1.25±0.66** 0.17±0.03** 0.04±0.03** Join scaling χ 2

            192 (p&lt;0.001)

            55.1 (p&gt;0.001) 26.6 (p&lt;0.001)

            7.75 NS 161.13 (p&lt; 0.001) Best fitted m 86.22±1.14** - 3.93±0.73** 14.26±1.43** - 2.73±0.01** [d]

          • 74.64±2.61** - - - - -0.36±0.08**

            [l] 6.20±4.73ns - -2.11± 1.24* 14.35 2.82** - 0.82 ±0.10** Join scaling b χ 2 0.117

          • 0.233 (p=0.629) 0.493 (p= 0.483)
          • 0.98 (p=0.321) Epistasis complement increaser - duplicate increaser duplicate decreaser - duplicate decreaser

            (p= 0.738)

            Parameter a Grain number (no) Grain yield (g) Cross 1 Cross 2 Cross 1 Cross 2

            Three parameter m 112.79±3.7** 68.58±2.1** 7.28±0.31** 6.07±0.29** [d] 61.00±3.8** 21.07±2.0** 3.36±0.30** 2.11±0.28** [h] 38.00±7.0** 4.68±4.1 ns 1.71±0.62** 2.85±0.57** Join scaling χ 2

            41.46 (p&lt;0.001) 54.0 (p&lt;0.001)

            41.56 (p&lt; 0.001) 52.75 (p&lt; 0.001)

            Best fitted m

            124.45±4.2** 78.85±2.4** 8.28±0.34** 7.50± 0.36** [d] 68.40±4.2** 26.55±2.4** 3.74±0.34** 2.91± 0.36** [h] -50.85±19.2** -61.01±9.1** -7.33±1.40** -5.20±1.33** [i]

            [j] -60.8±19.2** -18.88±8.4** -3.81±1.48** -3.35±1.22** [l] 99.95±17.7** 74.97±9.7** 11.61±1.63** 8.74±1.29** Join scaling b χ 2

            1.14 (p=0.286) 0.05 (p=0.815)

            3.03 (p=0.08) 1.60 (p=2.05)

            Epistasis duplicate decreaser duplicate decreaser duplicate decreaser duplicate decreaser Remarks: a Mean m, additive [d], dominance [h], additive x additive [i], additive x dominance [j], dominance x dominance [l], b

          χ2 test with 1 df for the 5 parameters model, *, and ** significantly different t-test from zero at 0.05, and 0,01, respectively, NS, non- significant,

            Table 3. (continued)

          • 0.80±0.48 ns
          • 2.42±0.35** - 0.30±0.01**
          • 0.96 (p=0.321) Epistasis - - duplicate decreaser duplicate decreaser - duplicate decreaser

          • 3.54±2.03 ns

            289 tira N ugraha et al .: Im pli c at ion of Gene Ac tio n and H eri tabilit y U nder St re s s and C on trol C ondit ions ……………….

            Tabel 4. Joint scaling test with three parameter model (m, [d], [h]) and estimates of the components of the six generation means of fitted to a six parameter model of rice population from the cross of Inpara5 x Mahsuri (Cross 1) and Inpara 5 x Pokkali (Cross 2) under control condition in the field

            Epistasis complement increaser - duplicate decreaser duplicate decreaser Remarks: a Mean m, additive [d], dominance [h], additive x additive [i], additive x dominance [j], dominance x dominance [l], b

          χ2 test with 1 df for the 5 parameters model, *, and ** significantly different t-test from zero at 0.05, and 0,01, respectively, NS, non- significant,

            0.19 (p=0.665) 0.37 (p=±0.542)

            0.21 (p=0.648) 0.018 (p=0.89)

            [j] 38.2±17.4** 19.44±5.2** - 2.66±1.36* [l] 65.58±15.4* - 11.11±3.51** 11.94±1.55** Join scaling b χ2

            177.9±2.3** 125.5±3.3** 16.33±2.17** 13.33±0.41** [d] 52.2±2.3** 1.09±1.5** -1.42±0.31** -1.87±0.41** [h] 29.98±14.3* 19.84±4.3** -10.47±5.5ns -8.143±1.6** [i]

            Best fitted m

            29.8 (P&lt;0.001) 62.3 (p&lt;0.001)

            16.02 (p=0.001) 20.61 (p&lt;0.001)

            Three parameter m 175.9±2.2** 134.98±1.2 14.10±0.31** 11.70±0.34** [d] 52.06±2.2** 13.94±1.2 -1.13±0.30** -1.50±0.32** [h] 20.14±4.6** 8.6±2.16 1.00±0.60 ns 2.86±0.64** Join scaling χ 2

            Parameter a Grain number (no) Grain yield (g) Cross 1 Cross 2 Cross 1 Cross 2

            Table 4. (continued)

            0.21 (p=0.647) 0.19 (P=0.663)

            2.72±1.19* - -0.36±0.08** [l] - - 9.98±2.11** 9.06±1.28** - 0.83±0.10** Join scaling b χ2

            [h] - - -4.63±2.10* -7.68±1.36** - -0.58±0.08** [i] - - - - - - [j]

            96.5 (p&lt;0.001) Best fitted m - - 15.40±0.48** 12.42±0.35** - 2.73±0.01** [d]

            NS

            34.6 (P&lt;0.001) 53.1 (p&lt;0.001)

            19.75±0.69** 17.43±0.87** 1.26±0.42** -1.94±0.28** -0.42±0.01** 0.27±0.01** [h] 18.02±1.18** 13.98±1.77** 4.17±0.76** 1.30±0.51* 0.28±0.02** 0.04±0.03 ns Join scaling χ 2 NS NS

            Three parameter m 120.65±0.69** 121.86±0.91** 14.34±0.43** 11.05±0.29** 2.02±0.01** 2.69±0.01** [d]

            Parameter a Plant height (cm) Tiller Number (no) 100-grain weight (g) Cross 1 Cross 2 Cross 1 Cross 2 Cross 1 Cross 2

          • 10.11±3.8** -1.47±2.14ns -

            .…

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            Yudhistira Nugraha et al.: Implication of Gene Action and Heritability Under Stress and Control Conditions ……………

            Heritability

            Broad-sense heritability (h 2 bs) and narrow- sense heritability (h 2 ns ) of two crosses under control and iron toxicity condition are shown in Table 5.

            Most of characters in the two crosses had similar for board-sense heritability under iron toxicity and control condition ranging from 0.68 to 0.87. The Cross 1 showed slightly higher of h 2 bs compared to Cross 2, except for the grain yield. For the narrow-sense heritability under iron toxicity condition was lower (3% to 23%) compared to control condition indicating the environment influenced on the genetic variance of the parents and their offspring. Lower heritability under stresses condition was also reported in most of characters in soy bean in acidic soil (Kuswantoro, Basuki, &amp; Arsyad, 2011) and wheat in drought condition (Said, 2014). This phenomenon indicted that the variation of stressed site was larger compared to the control condition. Iron concentration in the soil solution can be vary in same topo-sequence because of difference of soil profile, other nutrient availability, and reduced microbial activity (Becker &amp; Asch, 2005).

            The difference of soil conditions of the two plots, probably contributed to lower value of estimated of broad-sense heritability and narrow- sense heritability in the iron-stress condition compared to normal condition. Meanwhile, the narrow-sense heritability had lower compared to broad sense heritability in both conditions. This was caused by lower proportion of heritable variance (additive variance) compared to total genetics variance, which could be explained also by a complex gene action in the in heritance of most of characters. The broad-sense heritability measures phenotypic variance, while narrow-sense heritability measures the proportion additive variance (heritable variance) to total genetic variance (Fehr, 1987).

            This research also described the relation- ship of stress index and heritability, where the less affected to stress in particular characters the higher the estimates of heritability. An example was found in 100-grain weight of the Cross 1, which the STI was near to 1 and the h 2 bs 84%. This relation also related to its gene action, which simple additive- dominant model was fit for explaining the mode of inheritance (Table 3 and Table 4). The grain weight is related to consumer preference involving dimension and shape of the grain. Since the inheritance relatively simple to get desirable grain weight the selection can be done whether under control or iron toxic condition. The simple gene effect and high heritability in grain weight was also reported in genetic study in rice for blast resistant (Divya et al., 2014) and salinity tolerance (Mohammadi, Mendioro, Diaz, Gregorio, &amp; Singh, 2014).

            Correlation among Characters of F 2 Population

            Relationship of leaf bronzing Score (LBS), plant height, tiller number, 100-grain weight were estimated in the F 2 population under iron toxicity stress and control. Variation of LBS was only found under toxicity condition. We included this character in correlation analysis but not in the previous genetics parameters analysis because it does not meet requirement the control distribution data. LBS was highly negative correlated grain yield, 100- grain weight, plant height in Cross 2, while the Cross 1 only in the grain yield.

            291

            0.11 0.20* -0.36** 1.00

            Malaysian traditional variety that reported small with high-density grain (Suhartini &amp; Makarim 2009). Meanwhile, the sensitive parent, Inpara5 is semi-dwarf plant type that inserting a submergence tolerance gene, SUB1 (Septiningsih et al., 2015). The aim of this cross is to combine those important traits as well as iron toxicity tolerant into the agronomical farmer accepted plant type like Inpara5. Hence, based on those characteristic of the parents, combining Fe toxicity tolerance with other important traits can be done concurrently, resulting a multi-tolerance stress rice variety.

            Improvement grain yield in iron toxicity affected area needs effective and efficient breeding methods. In this study revealed that the to salinity (Gregorio et al., 2002), Mahsuri is a

            Implication for Selection Iron Toxicity Tolerant in Rice

            The grain yield was correlated positively in all characters in the Cross2 except for grain number, while in the Cross 1 was correlated only with the plant height and grain number under toxicity condition (Table 6). Meanwhile under control condition, the positive correlation of grain yield was found only in the Cross 1 with plant height and tiller number. A significant positive correlation of plant height with 100-grain weight was found in Cross 1 both under iron toxicity (r=0.55**) and control (r=0.52**) condition, while for the Cross 2 was found in different direction (iron toxicity =-0.44**, control=-0.17). The grain number of Cross 1 correlated negatively with 100- grain weight both under iron toxicity and control condition.

            

          Remarks: LB= Leaf Bronzing Score, PH= plant height, TN= tiller number, HG= 100-grain weight, GY= grain yield; The

          r coefficient above the horizontal is Cross of Inpara5 x Pokkali and r coefficient under the horizontal is Cross of Inpara5 x Mahsuri; * and ** are significant of t-test at 0.05 and 0.01, respectively

            0.17 0.67 -0.19 -0.48** 1.00 -0.01 GY -0.27** 0.08 0.32** -0.41** 0.89** 1.00 0.31** 0.84** -0.01 0.16 1.00

            0.15 1.00 -0.02 0.30** 0.05 HG -0.09 -0.41** 0.08 1.00 0.60** 0.36** -0.17 -0.11 1.00 0.04 -0.09 GN -0.29

            Yudhistira Nugraha et al.: Implication of Gene Action and Heritability Under Stress and Control Conditions ……………

            0.16 1.00 -0.02 -0.13 0.53**

            0.05 TN -0.06

            1.00 0.15 0.52** 0.17

            LB 1.00 -0.26** -0.04 -0.36** -0.25** -0.24** - - - - - PH -0.10 1.00 0.17 0.55** 0.88** 0.34**

            Characters Iron Toxicity Control LB PH TN HG GN GY PH TN HG GN GY

            Table 6. Simple correlation among characters in F 2 individuals under iron toxicity and control condition in two crosses

            This genetic study revealed a complex gene action involving epistasis duplicate decreaser and low heritability, indicating that the selection should be postponed in later generation to allow favorable gene are fixed (Fehr, 1987; Kearsey &amp; Ponni, 1996). On the other hand, this result also showed that the lesser environment for selection affected to stress (control condition) the

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            Yudhistira Nugraha et al.: Implication of Gene Action and Heritability Under Stress and Control Conditions ……………

            favor gene for good agronomy performance, yield components and grain yield. Thus, this selection can be done in normal condition. Meanwhile, under iron toxic-location or other stressed location can be done for selection of the tolerant- stress progenies.

            This study also reported some characters that related to degree of tolerance under iron toxicity condition. The scoring method using visualization of leaf bronzing has been developed by IRRI using standard evaluation system for rice (IRRI, 1996) to score the degree of tolerance and used in the breeding program. It has been reported that under field condition each visual symptom score increase was associated with a yield loss of approximately 400 kg ha

            −1

            (Audebert &amp; Fofana, 2009). Thus, it was considered that leaf bronzing score (LBS) as a relevant trait for the screening of tolerance to Fe toxic conditions as described significant correlation between LBS and grain yield in this study (Table 6). However, the genetics analysis needs quantitative data that could not fulfilled by LBS. Hence, the other characters that might had relationship with the tolerance is needed. It was found that tiller number, number grains for the Cross 1, while for the Cross 2, plant height, tiller number, 100-grain weight could be used as a selection criteria for both of grain yield and LBS in the two crosses under iron toxicity condition.

            The linked DNA markers selection can be used to select the rare recombinants and combined the favorable alleles. However, some QTLs studies for Fe toxicity tolerance have been reported low association with phenotypical traits, indicating that challenges to localize the marker with several tolerant parents, Mahsuri and Pokkali displaying high value of STI compared to sensitive parent,

            Inpara5 in all characters. The mid-parent

            heterotics in F 1 STI were also found in all characters. The STI of F 2 generation was between the two parents; while the STI value of the back crosses generation (BC1P 1 and BC1P 2 ) followed the direction of their recurrent parent.

            The grain yield and others agronomical characters were not fitted to simple model of additive-dominance, indicating the presence of allelic interaction. Further analysis revealed that the five parameter models with epistasis duplicate and complementary gene action were fitted to explain the gene action model. The direction of most characters toward decreasers with high interactive of dominant x dominant. The estimates heritability’s under control condition were higher compared to iron toxicity condition. Meanwhile, under both sites show that the Cross 1 had the greatest chance of genetic improvement in all characters observed under iron toxicity condition, while the Cross 2 had the greatest chance under normal condition. This result suggests that the successful of breeding program is influenced by the appropriate selection of the parents and selection environment. Delaying the selection to later generations by maintaining larger populations combined with the shuttle breeding selection in normal condition for accepted-agronomical traits could be proposed as the best breeding strategy for improving yield and tolerance to iron toxicity.

            ACKNOWLEDGEMENT The authors deeply acknowledge to Dr.

            Nafisah, Ms. Trias Sitaresmi and Mr. Subardi for

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